harishpj

• Jain, Harish Pruthviraj; Ho, Richard David Jun-Geet & Angheluta, Luiza (2025). Emergent cell migration from cell shape deformations and T1 transitions. Physical Review Research (PRResearch). 7(3). doi: 10.1103/d6qj-775d. Full text in Research Archive Show summary

  T1 transitions—cell neighbor exchanges—are key drivers of tissue remodeling and fluidization in epithelial monolayers. Using a multiphase field (MPF) model that accounts for dynamic cell shapes, alongside an active elastic solid model lacking cell shape degrees of freedom, we study the spatiotemporal organization of T1 transitions. While individual T1 transitions occur as a Poisson process in time, their spatial distribution is strongly influenced by local cell shape deformations. We identify a dual mechanical response: cells losing neighbors tend to relax their shape isotropically, whereas cells gaining neighbors undergo anisotropic elongation. By analyzing successive T1 events in the MPF model, we find asymmetric spatial patterns that depend on whether a cell gains or loses neighbors. These asymmetries lead to persistent, localized directional motion, even in the absence of external cues. Our results suggest an intrinsic mechanism for directed cell migration driven by local topological rearrangements mediated by cell shape dynamics—a process potentially relevant for epithelial flows during development, morphogenesis, and wound healing.

• Jain, Harish Pruthviraj; Voigt, Axel & Angheluta-Bauer, Luiza (2024). From cell intercalation to flow, the importance of T1 transitions. Physical Review Research (PRResearch). 6(3). doi: 10.1103/PhysRevResearch.6.033176. Full text in Research Archive Show summary

  T1 transitions, also called cell intercalations, are important sources of fluidization of epithelial cell monolayers. We use a multiphase field model to quantify this tissue fluidization in terms of the relative dispersion of cells and characterize the T1 flow profile. We show that the ensemble-averaged flow profile of a T1 transition has a saddle-point pattern accompanied by a localized burst in cell speed. Although the temporal evolution of the relative dispersion of cells depends on specific model details, the different dispersion curves collapse robustly onto a linear function of the number of T1 transitions, implying an important connection between T1 transitions and mixing in dense systems.

• Syga, Simon; Jain, Harish Pruthviraj; Krellner, Marcus; Hatzikirou, Haralampos & Deutsch, Andreas (2024). Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy. PLoS Computational Biology. ISSN 1553-734X. 20(8). doi: 10.1371/journal.pcbi.1012003. Full text in Research Archive Show summary

  Cancer is a significant global health issue, with treatment challenges arising from intratumor heterogeneity. This heterogeneity stems mainly from somatic evolution, causing genetic diversity within the tumor, and phenotypic plasticity of tumor cells leading to reversible phenotypic changes. However, the interplay of both factors has not been rigorously investigated. Here, we examine the complex relationship between somatic evolution and phenotypic plasticity, explicitly focusing on the interplay between cell migration and proliferation. This type of phenotypic plasticity is essential in glioblastoma, the most aggressive form of brain tumor. We propose that somatic evolution alters the regulation of phenotypic plasticity in tumor cells, specifically the reaction to changes in the microenvironment. We study this hypothesis using a novel, spatially explicit model that tracks individual cells’ phenotypic and genetic states. We assume cells change between migratory and proliferative states controlled by inherited and mutation-driven genotypes and the cells’ microenvironment. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. Notably, different genetic configurations can result in this pattern of phenotypic heterogeneity. We analytically predict the outcome of the evolutionary process, showing that it depends on the tumor microenvironment. Synthetic tumors display varying levels of genetic and phenotypic heterogeneity, which we show are predictors of tumor recurrence time after treatment. Interestingly, higher phenotypic heterogeneity predicts poor treatment outcomes, unlike genetic heterogeneity. Our research offers a novel explanation for heterogeneous patterns of tumor recurrence in glioblastoma patients.

• Jain, Harish Pruthviraj; Voigt, Axel & Angheluta-Bauer, Luiza (2023). Robust statistical properties of T1 transitions in a multi-phase field model of cell monolayers. Scientific Reports. 13. doi: 10.1038/s41598-023-37064-6. Full text in Research Archive Show summary

  Abstract Large-scale tissue deformation which is fundamental to tissue development hinges on local cellular rearrangements, such as T1 transitions. In the realm of the multi-phase field model, we analyse the statistical and dynamical properties of T1 transitions in a confluent monolayer. We identify an energy profile that is robust to changes in several model parameters. It is characterized by an asymmetric profile with a fast increase in energy before the T1 transition and a sudden drop after the T1 transition, followed by a slow relaxation. The latter being a signature of the fluidity of the cell monolayer. We show that T1 transitions are sources of localised large deformation of the cells undergoing the neighbour exchange, and they induce other T1 transitions in the nearby cells leading to a chaining of events that propagate local cell deformation to large scale tissue flows.

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• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2024). Active Reorganisation in Tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2024). Active Reorganisation in Tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Active Reorganisation in Tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Active Reorganisation in Tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Energy profiles and statistics of spontaneous T1 transitions in confluent tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Robust statistical properties of T1 transitions in confluent tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Active Reorganisation in Tissues. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2023). Active Reorganisation in Tissues: Phase Transition of Ideas from Physics to Biology. Full text in Research Archive
• Jain, Harish Pruthviraj; Angheluta, Luiza & Voigt, Axel (2022). Phasefield Model of Active Interacting Cells that Grow and Divide. Full text in Research Archive Show summary

  Contact inhibition limits migration and proliferation of cells in cell colonies. We consider a multiphase field model to investigate the growth dynamics of a cell colony, composed of proliferating cells. The model takes into account the mechanism of contact inhibition of proliferation by local mechanical interactions. We compare nonmigrating and migrating cells, in order to provide a quantitative characterization of the dynamics and analyze the velocity of the colony boundary for both cases. Additionally, we measure single cell velocities, number of neighbor distributions, as well as the influence of stress and age on positions of the cells and with respect to each other.

• Jain, Harish Pruthviraj (2025). Collective emergent behaviour of active cellular systems. University of Oslo (UiO). Full text in Research Archive Show summary

  Using multi-phase field models, we study the collective emergent behavior of a monolayer of active, deformable interacting cells, with an emphasis on neighbour exchange process involving four cells called T1 transition, also known as cell intercalation. The cells undergo drastic shape deformations during T1 transitions, leading to a buildup of energy prior to the T1 transitions and a subsequent release of energy post T1 transitions near the sites where junctions remodel. These deformations have a dual impact: cells losing neighbours relax their shapes, while cells gaining neighbours elongate. T1 transitions contribute to a transient quadrupolar flow field where the cells undergoing these transitions acquire high speeds. The relative dispersion of cells within a monolayer is solely determined by the cumulative number of T1 transitions, highlighting the importance of T1 transitions in mixing of cells. By analyzing the spatial relationships between successive T1 transitions undergone by a cell, we observe an emergent directional migration of cells that depends on the underlying topological changes in the neighborhood. Lastly, we utilize Minkowski Tensor-based p-atic order parameters as robust shape descriptors to describe cell shape rotational symmetries in both experimental and simulated monolayers.

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